MLOps Engineer (Remote)
Hire Feed · Latin America
- Hybrid
- Part-time
- $78,000 / year
- Latin America
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Job highlights
- Evaluate AI agents and train LLMs.
- Assess production-grade software architecture.
- Provide technical feedback for LLM training.
- Requires backend, AI automation, or systems integration experience.
- Work remotely with flexible task assignments.
About the role
MLOps Engineer (Remote)
Location: Remote (LATAM, Puerto Rico, Argentina, Peru, Colombia, Brazil, Mexico, Chile, Bolivia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Nicaragua, Panama, Paraguay, Trinidad and Tobago, Uruguay, Venezuela)
Work Mode: Fully Remote
Role Overview
Help design and evaluate autonomous AI agents across multiple LLMs, spanning health, education, daily life, and other real-world domains (all coding work). Shape the future of agentic AI systems by providing expert human feedback to leading AI organisations. Help train Large Language Models (LLMs) for complex, multi-step architectural workflows.
Key Responsibilities
AI Agent Evaluation
- Write evaluation rubrics with objective pass/fail criteria
- Debug agent traces to identify failure patterns
- Stress test agents against edge cases, prompt injection, and tool misuse
Technical Assessment
- Assess production-grade modular software architecture
- Analyse multi-turn system interactions and behaviours
- Provide high-density technical feedback for LLM training
Project Workflow
- Create an account and upload a resume/ID
- Complete the onboarding assessment
- Start earning through flexible task assignments
Qualifications
- Experience in backend engineering, AI automation, or complex systems integration
- Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting)
- Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases
- Practical experience building for live, non-mocked environments and handling multi-turn system interactions
Preferred (Nice to Have)
- Experience integrating agents with live tools such as Supabase, Gmail, and other APIs
- Familiarity with persistent state and session-tracking patterns
- Experience identifying privacy leaks, authority escalation, or indirect prompt injection vulnerabilities
Compensation
Hourly compensation ranges from USD $30–$50, depending on experience and task complexity. Payments are issued weekly via supported payout platforms (e.g., PayPal or AirTM). Full compensation details are provided prior to task acceptance.
Equal Opportunity Statement
Selection decisions are based solely on skills, qualifications, and project requirements. We are committed to inclusive and fair engagement practices and consider all qualified applicants without regard to legally protected characteristics.
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Key skills/competency
- MLOps Engineer
- AI Agents
- Large Language Models (LLMs)
- Backend Engineering
- Software Architecture
- Python
- SQL Databases
- System Integration
- AI Automation
- Remote Work
Skills & topics
- MLOps Engineer
- AI Agents
- LLM Training
- Backend Engineering
- Software Architecture
- Python
- SQL
- System Integration
- AI Automation
- Remote
How to get hired
- Tailor your resume: Highlight backend engineering, AI automation, and complex systems integration experience.
- Showcase technical skills: Emphasize proficiency in Python, JavaScript, Go, or Java, and SQL database experience.
- Demonstrate live environment experience: Detail your work with non-mocked environments and multi-turn system interactions.
- Prepare for onboarding: Be ready to complete an assessment to showcase your abilities.
- Understand the role: Research AI agent evaluation and LLM training to align your application.
Technical preparation
Practice Python, JavaScript, Go, or Java.,Build projects using SQL databases.,Develop modular software architectures.,Simulate live environment interactions.
Behavioral questions
Describe a complex system you engineered.,How do you debug agent traces?,How do you provide constructive feedback?,How do you handle edge cases?
Frequently asked questions
- What is the MLOps Engineer role at Hire Feed about?
- The MLOps Engineer role at Hire Feed focuses on designing and evaluating autonomous AI agents across various LLMs and domains. You'll provide human feedback for AI training and help develop complex architectural workflows.
- Is the MLOps Engineer position remote?
- Yes, the MLOps Engineer position at Hire Feed is fully remote. It is open to candidates located in LATAM, Puerto Rico, and specific countries within those regions.
- What are the primary responsibilities of an MLOps Engineer at Hire Feed?
- Key responsibilities include writing evaluation rubrics, debugging agent traces, stress testing AI agents, assessing software architecture, analyzing system interactions, and providing technical feedback for LLM training.
- What qualifications are essential for the MLOps Engineer role at Hire Feed?
- Essential qualifications include experience in backend engineering, AI automation, or complex systems integration, proficiency in at least two major programming languages (Python, JavaScript, Go, Java), and experience with SQL databases and live environments.
- What preferred skills would benefit an MLOps Engineer applicant at Hire Feed?
- Preferred skills include experience integrating agents with live tools (Supabase, Gmail, APIs), familiarity with persistent state and session-tracking, and experience identifying privacy leaks or prompt injection vulnerabilities.
- How is compensation determined for the MLOps Engineer role at Hire Feed?
- Compensation is hourly, ranging from USD $30-$50, based on your experience and the complexity of the tasks. Full compensation details are provided before task acceptance.
- How can I apply for the MLOps Engineer job at Hire Feed?
- To apply, you'll need to create an account on the Hire Feed platform, upload your resume and ID, and complete their onboarding assessment. Specific application instructions are provided within the job posting.
- What is the work mode for this MLOps Engineer position?
- The work mode is fully remote, offering flexibility for candidates in the specified LATAM regions and Puerto Rico.